Geophysical Imaging and Monitoring
Andrea Balza Morales
M.Sc.
Andrea Balza Morales
PhD researcherM.Sc. Andrea Balza Morales
Geophysical Imaging and Monitoring
RWTH Aachen University
Wüllnerstr. 2 (Bergbaugebäude)
Room: 505d
52062 Aachen
Research Interests
- Gravity and magnetic data processing and inversion
- Time-lapse monitoring techniques
- Structure-based inversion
- 3D Geological modeling
- Geothermal exploration using joint interpretation and inversion
Professional experience
| 2021 – present | PhD Researcher at RWTH Aachen and ETH Zürich within the MSCA Action EASYGO |
| 2013 – 2021 | Geophysical Data Processor at EDCON-PRJ Inc (Denver, Colorado) |
| 2016 – 2017 | Graduate Research Assistant at Colorado School of Mines (Golden, Colorado) |
Education
| 2014 – 2017 | Masters of Geophysics (M.Sc.) at Colorado School of Mines (Golden, Colorado) |
| 2012 – 2013 | International Exchange Program at University of New Mexico (Albuquerque, New Mexico) |
| 2008 – 2013 | Geophysical Engineering (B.Sc.) at Universidad Simon Bolivar (Caracas, Venezuela) |
Awards and service to profession
| 2012 – 2013 | Mendenhall Prize for Outstanding Graduating Master of Science Students, Department of Geophysics, Colorado School of Mines. Denver, Colorado |
| 2004 – 2005 | All-American Scholar award, United States Achievement Academy. Miami, Florida |
| 2020 – 2022 | Serving Chair, Geophysical Society of Houston, Potential Field Special Interest Group |
| 2021 | Membership Committee, EEGS, Environmental and Engineering Geophysical Society |
| 2020 – 2021 | Coding Group Leader, GeoLatinas - Latinas in Earth and Planetary Sciences |
Publications
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Integrating time-lapse gravity, production, and geological structure data in a gas reservoir study
2020 |
Interpretation, doi:10.1190/int-2019-0272.1
Note: This publication resulted from Andrea's master thesis i.e. was prepared before GIM was founded.Abstract
Time-lapse gravity is most commonly used to monitor fluid movement and is especially useful when monitoring water encroachment in a gas reservoir. Although time-lapse gravity data are directly sensitive to the fluid saturation changes in reservoirs, it is still necessary to integrate multiple types of data with complementary information to enhance the time-lapse gravity interpretation. When monitoring water-influx in a reservoir, the changes in water yield in production wells may directly indicate saturation changes with time and provide such complementary information about the areas of fluid movement. We present a workflow to invert a time-lapse gravity data set and production data to help monitor the edge water encroachment through a case study at the Sebei gas field in Western China. Three time-lapse gravity surveys were acquired between 2011 and 2013 and production data were also collected from 286 wells during the same period of time. We integrate the two data sets and the structural information in the reservoir through a framework of constrained time-lapse gravity inversion. In this workflow, we incorporate the information from the production data into the inversion by converting the gas and water yield into a reference model. We also incorporate geological structural information through spatially varying bound constraints. Through this approach, we construct a set of time-lapse density contrast models that are consistent with the time-lapse gravity data, production data, and structural information. The resultant density contrast models better delineate the regions of the reservoir with increased water influx and also enable us to produce improved porosity estimations in the reservoir.
Cite as
Balza Morales, A. and Li, Y. (2020): Integrating time-lapse gravity, production, and geological structure data in a gas reservoir study. Interpretation. https://doi.org/10.1190/int-2019-0272.1
Conference contributions
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The site selection data hub: a data-centric approach for integrated simulation workflow management in radioactive waste disposal site selection
2024 |
EGU General Assembly, Vienna, 14-19 April 2024
Conference websiteAbstract
Given the importance of ensuring the safe disposal of radioactive waste, it is vital to understand the targeted subsurface systems and to build physics-based models to predict their dynamic responses to human interventions. Constructing robust predictive models, however, is very challenging due to the systems' complexity as well as the scarcity and cost of geophysical data acquisition. Optimal matching of data acquisition and predictive simulations is therefore necessary and can be achieved via integrating predictive process modeling, Bayesian parameter estimation, and optimal experimental design into a modular workflow. This allows to quantify the information content of measurement data and therefore enables optimal planning of data acquisition and monitoring strategies. Conducting such data-integrated simulation studies, however, requires a robust workflow management that ensures reproducibility, error management, and transparency. To meet this demand, we established a data-centric approach to workflow control combining error-managed simulations with a functional data hub, providing simulations with direct access to a database of essential material properties. The latter are being made available as site specific scenario compilations along with uncertainty margins and meta information. The data hub serves as an interface facilitating seamless data and simulation exchange to support subsequent model-driven decision-making processes and guarantees that simulations are conducted using manageable, comparable, and reproducible test cases. Furthermore, it ensures that the simulation results can be readily transferred to a designated repository allowing for real-time updates of the model. The implementation of the data hub is based on a Python-based framework for two different use cases: 1) GUI-based use case: The graphical user interface (GUI) facilitates data import, export, and visualization, featuring distinct sections for geographic data representation, structured table organization, and comprehensive visualization of physical properties in varying dimensions. 2) Module-based use case: Built on the YAML-based data-hub framework, it enables direct integration of simulation modules storing measurements and model parameters in the YAML data format. The data is systematically organized to furnish a versatile data selection framework that allows information to be extracted from a variety of references, including specific on-site measurements, laboratory measurements and other references, thereby enabling a comprehensive exploration of different reference-oriented scenarios. This study showcases the data hub as a management infrastructure for executing a modular workflow. Multiple models—such as process and impact models as well as their surrogates and geophysical inverse models—are generated within this workflow utilizing scenarios provided by the data hub. Our study shows that adopting a data-centric approach to control the simulation workflow proves the feasibility of conducting different data-integrated simulations and enhances the interchangeability of information across different stages within the workflow. The paradigm of sustainable model development ensures reproducibility and transparency of our results, while also offering the possibility of synergetic exchange with other research areas.
Cite as
Chen, Q. and Boxberg, M. S. and Menzel, N. and Morales Oreamuno, M. F. and Nowak, W. and Oladyshkin, S. and Wagner, F. M. and and Kowalski, J (2024): The site selection data hub: a data-centric approach for integrated simulation workflow management in radioactive waste disposal site selection. EGU General Assembly, Vienna, 14-19 April 2024.
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Ein Exponat zur Veranschaulichung von seismischen Wellen für die Öffentlichkeitsarbeit
2024 |
84. Jahrestagung der Deutschen Geophysikalischen Gesellschaft, 10.-14. März, Jena
Conference websiteNote: This conference contribution resulted from a hands-on geophysical experiment at the RWTH science night in November 2023.Abstract
Die Vorführung von seismischen Experimenten in Innenräumen für die Öffentlichkeitsarbeit ist oftmals nicht direkt möglich. Idealisierungen oder Miniaturisierungen sind in solchen Fällen erforderlich. Daher haben wir ein Exponat zur Veranschaulichung von seismischen Wellen in Tischgröße konzipiert. Mit unterschiedlich schweren und großen Fallgewichten, die von einem Gestell aus verschiedenen Höhen fallen gelassen werden, können seismische Wellen erzeugt und mit einem RaspberryShake aufgezeichnet werden. Es wurden verschiedene Materialien (Sand, Schaumstoff und Styropor) verwendet, um deren Einfluss auf die Wellenform zu illustrieren. Für die Aufzeichnung und Visualisierung wurde eine Webapplikation entwickelt, welche die Daten des RaspberryShakes kontinuierlich anzeigte. Dazu wurde über einen STA-LTA-Trigger eine Aufzeichnungsmöglichkeit implementiert, so dass verschiedene Seismogramme verglichen werden konnten. Darüber hinaus wurden Gamification-Elemente eingebaut. So konnten Teilnehmer versuchen vorab aufgezeichnete Seismogramme zu reproduzieren. Außerdem konnten, ähnlich wie bei der Jahrmarktattraktion Hau den Lukas, Signale einer bestimmten Stärke erzeugt werden. Hier sollte dann aber nicht eine möglichst starke Amplitude erzeugt werden, sondern eine vorgegebene Amplitude möglichst genau getroffen werden. Ergänzend wurden noch didaktisch aufbereitete Materialien zur Erklärung von aktiver Seismik und der Untergrunderkundung geliefert. Das Exponat wurde bereits erfolgreich auf der RWTH-Wissenschaftsnacht 5 vor 12 im Herbst 2023 eingesetzt und wird stetig weiterentwickelt.
Cite as
Boxberg, M. S. and van Meulebrouck, J. and Balza Morales, A. and Menzel, N. and Wagner, F. M. (2024): Ein Exponat zur Veranschaulichung von seismischen Wellen für die Öffentlichkeitsarbeit. 84. Jahrestagung der Deutschen Geophysikalischen Gesellschaft, 10.-14. März, Jena.
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Geothermal potential in the Rhine-Ruhr region - Integration of structural analysis and a preliminary magnetotelluric feasibility study
2022 |
European Geothermal Congress, Berlin, 17.-21. Oct. 2022
Abstract
Geothermal systems often occur in geologically complex structural environments with many closely spaced and intersecting faults. These commonly control the associated fluid flow needed for conventional geothermal reservoirs. One of the goals of the Innovative Training Network EASYGO - Efficiency and Safety in Geothermal Operations, aims to better characterize these systems in order to provide an initial assessment of geothermal potential in Europe. The Rhine-Ruhr region was selected as an area of interest for geothermal energy use in the context of the energy and heat transformation change in former coal mining areas. Here, Devonian carbonates and sandstones could play a role as potential reservoirs associated with karst systems or/and fracture zones. The magnetotelluric method has proven to be a useful tool in geothermal plays, where conductive bodies exist at depth. The goal of this study is to identify the structures and associated areas with enhanced fluid flow using structural analysis and magnetotelluric (MT) data. The initial areas chosen in the Rhine-Ruhr region were Rheindahlen, Lüdenscheid, and Aachen. Their local geology confirms favorable conditions for geothermal reservoir development. Additionally, these zones are strategic for MT data acquisition because of their distance from potential sources of anthropogenic noise. The study focuses on a quantitative method for fracture analysis attributes of potential reservoir rocks along with the integration of the geology, fault response modeling, and stress analysis. In addition, we plan to carry out an MT survey integrating the three areas of interest using prior geologic information. For this, we conducted a 3D forward modeling study to simulate the expected MT signals based on the initial structural analysis of the areas of interest. This was done as a feasibility study to predict if the calculated MT signal will be of sufficient signal-to-noise ratio to carefully design future MT acquisition campaigns. Results show favorable structural settings for the transport of fluids (e.g., fault intersection), where the structural component is marked by NW-SE striking normal faults and NE-SW oriented thrust faults with a strike slip-dilation component. Preliminary fracture analysis observed on the surface supports hints of density fracture zones for water circulation, but further studies should be conducted to see if these fractures propagate at depth. The synthetic MT study shows that a considerable signal is expected from conductive bodies within the range of 3,500 to 4,000 m depth. The characterization of the reservoir potential in these areas will facilitate similar studies in the entire Rhine-Ruhr region for a better understanding of the geothermal potential of North Rhine-Westphalia. This project has received funding from the European Unions Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 956965.
Cite as
Balza Morales, A. and Gomez Diaz, E. and Brehme, M. and Kukla P. A. and Wagner, F. M. (2022): Geothermal potential in the Rhine-Ruhr region - Integration of structural analysis and a preliminary magnetotelluric feasibility study. European Geothermal Congress, Berlin, 17.-21. Oct. 2022.
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Towards structure-based joint geological-geophysical inversion for improved characterization of geothermal reservoirs
2022 |
EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022
Conference websiteAbstract
Proper characterization of geologic structures that host geothermal systems is crucial for the efficiency and safety of their energy production. This includes estimating layer boundaries, complex geologic features, and lithology through means of inversion and its regularization. However, existing advanced regularization techniques (e.g., geostatistical regularization, minimum-gradient support, etc.) fail to capture the complexity of 3D geological models including fault networks, fault-surface interactions, unconformities, and dome structures. Förderer et al (2021) propose a solution by means of structure-based inversion, which implements implicit geological modeling and low-dimensional parametrization to produce sharp subsurface interfaces in 2D. This work aims to extend their approach to image realistic and complex geometries in 3D. We continue with the example of electrical resistivity tomography (ERT) and synthetic data; however, this approach is aimed towards independent and joint inversion of geophysical methods that are commonly used in geothermal exploration such as magnetotellurics, gravity, and seismic techniques. The 3D geological model is created using GemPy, an open-source Python library, which constructs a structural geological model from interface points and orientations using an implicit approach based on co-kriging (de la Varga et al., 2019). Subsequently, the 3D model is discretized, and physical parameters are assigned using minimal pilot points that are then interpolated. We use pyGIMLi (Rücker et al., 2017), another open-source multi-method library for geophysical modelling and inversion, to perform a structure-based inversion, where we include the interface points in the primary model vector of the inversion to update these points iteratively to estimate a geological model in agreement with the geophysical observations. In this work, special focus is placed on the sensitivity of each model parameter. To maintain low parametrization and account for the increase in computational power, the cumulative sensitivity is calculated and tested under criteria to optimize the model updates. This is relevant for geometries where the interface and pilot points are more influential in one dimension than others. The workflow has also been adapted to include more complex structures that can be defined in 3D, especially those that reflect geothermal systems. This work is part of the Innovative Training Network EASYGO (www.easygo-itn.eu), which aims to improve the efficiency and safety of geothermal operations but can be readily used in other applications. References: Förderer, A., Wellmann, F., and Wagner, F.M.: Geoelectrical imaging of subsurface discontinuities and heterogeneities using low-dimensional parameterizations, EGU General Assembly 2021, online, 19-30 Apr 2021, EGU21-10012, https//doi.org/10.5194/egusphere-egu21-10012, 2021. de la Varga, M., Schaaf, A., and Wellmann, F., 2019. GemPy 1.0: open-source stochastic geological modeling and inversion, Geosci. Model Dev., 12, 1-32, doi 10.5194/gmd-12-1-2019. Rücker, C., Günther, T., Wagner, F.M., 2017. pyGIMLi: An open-source library for modelling and inversion in geophysics, Computers and Geosciences, 109, 106-123, doi 10.1016/j.cageo.2017.07.011.
Cite as
Balza Morales, A. and Gomez Diaz, E. and Brehme, M. and Kukla P. A. and Wagner, F. M. (2022): Towards structure-based joint geological-geophysical inversion for improved characterization of geothermal reservoirs. EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022.